European and North American Advanced Driver Assistance Systems (ADAS) and High Definition (HD) Mapping Market, 2018
Published on: 09-Apr-2019 | SKU: AU01822-NA-MR_23010

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In today’s world, while robots have the capability to do some things more efficiently than humans, humans are still much wiser when it comes to real-time decision-making capability. One such application that comes to light is driving and navigation. For example, decisions, such as stopping the vehicle at the right place, watching for a traffic signal at the intersection, or avoiding a split at the last minute, which humans take for granted, are still much harder for robots to make.

In the near future, when cars start driving themselves, they will have to ‘see’ what is around them to maneuver leaving no room for errors. To achieve this, vehicles will not only rely on sensors but will also require machine-readable maps of the world, containing accurate and precise road information. Autonomous vehicles will use sensors to make driving decisions on the fly, but vehicle sensors cannot observe everything all the time. Vehicle sensors can be blinded by corners, other vehicles, or bad weather conditions. Even though the sensors may notice an obstacle, they may not do so early enough to make decisions. In addition, lanes and signs may be missing on the road or knocked over or hidden by bushes, and therefore, can go undetected by sensors. Such accidents will be averted when sensor data will be combined with map data.

Research Highlights

This research service provides an overview of the mapping market along with the differentiation between the types of maps and levels of autonomy that they will support. In addition to the overview, the study covers the components and attributes of ADAS and HD maps, which will help an autonomous vehicle to operate safely.

In conjunction with different processes of mapping, major HD map developers have been segmented on the basis of the mapping process they follow and compared on the basis of various assessment criteria, such as localization accuracy, the technology used for developing HD maps and needed by customers, current partnerships, and cost of acquiring the solution for a customer.

Key Issues Addressed

  • How will ADAS and HD maps enable safe operation of an autonomous vehicle?
  • How are ADAS maps different than HD maps, and why will HD maps replace ADAS maps for L4 and L5 autonomy?
  • What are the different processes that traditional map makers and start-ups follow to build HD maps?
  • Which are the different solutions offered by map-making companies, and how do they fare against each other?
  • Which are the OEMs and other customers that these HD map developers have partnered with, for development and testing?

Levels of Autonomy and Maps

HD Mapping Segments

Comparative Analysis—End-to-end Base Maps and Updates

Comparative Analysis—Crowdsourced Data Collection for Updates

Comparative Analysis—In-house Maps With Full Stack AV Software

Key Conclusions

Research Scope

Research Aims and Objectives

Key Questions this Study will Answer

Research Methodology

SAE Definitions

Parameters to Compare Profiles

SD, ADAS, and HD Maps

Autonomous Vehicles and ADAS and HD Maps

Elements of HD Maps

HD Mapping Process

HD Mapping Tools

Importance of an HD Base Map

Segmentation of Mapping Companies

End-to-end Mapping Companies

Crowdsourced Mapping Companies

In-house Mapping Companies

HERE Overview

HERE Overview (continued)

TomTom Overview

TomTom Overview (continued)

Civil Maps Overview

Civil Maps Overview (continued)

CARMERA Overview

CARMERA Overview (continued)

Sanborn Map Company Overview

Sanborn Map Company Overview (continued)

Voxelmaps Overview

Voxelmaps Overview (continued)

Mobileye Overview

Mobileye Overview (continued)

DeepMap Overview

DeepMap Overview (continued)

Mapper.ai Overview

Mapper.ai Overview (continued)

Mapbox Overview

Mapbox Overview (continued)

Waymo Overview

Waymo Overview (continued)

Oxbotica Overview

Oxbotica Overview (continued)

Drive.ai Overview

Drive.ai Overview (continued)

Growth Opportunity—Investments and Partnerships from OEMs/TSPs

Strategic Imperatives for Success and Growth

Key Conclusions

The Last Word—3 Big Predictions

Legal Disclaimer

Market Engineering Methodology

Abbreviations and Acronyms Used

List of Exhibits

List of Exhibits (continued)


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In today’s world, while robots have the capability to do some things more efficiently than humans, humans are still much wiser when it comes to real-time decision-making capability. One such application that comes to light is driving and navigation. For example, decisions, such as stopping the vehicle at the right place, watching for a traffic signal at the intersection, or avoiding a split at the last minute, which humans take for granted, are still much harder for robots to make. In the near future, when cars start driving themselves, they will have to ‘see’ what is around them to maneuver leaving no room for errors. To achieve this, vehicles will not only rely on sensors but will also require machine-readable maps of the world, containing accurate and precise road information. Autonomous vehicles will use sensors to make driving decisions on the fly, but vehicle sensors cannot observe everything all the time. Vehicle sensors can be blinded by corners, other vehicles, or bad weather conditions. Even though the sensors may notice an obstacle, they may not do so early enough to make decisions. In addition, lanes and signs may be missing on the road or knocked over or hidden by bushes, and therefore, can go undetected by sensors. Such accidents will be averted when sensor data will be combined with map data.--BEGIN PROMO--

Research Highlights

This research service provides an overview of the mapping market along with the differentiation between the types of maps and levels of autonomy that they will support. In addition to the overview, the study covers the components and attributes of ADAS and HD maps, which will help an autonomous vehicle to operate safely.

In conjunction with different processes of mapping, major HD map developers have been segmented on the basis of the mapping process they follow and compared on the basis of various assessment criteria, such as localization accuracy, the technology used for developing HD maps a

More Information
Deliverable Type Market Research
No Index No
Podcast No
Author Ayan Biswas
Industries Automotive
WIP Number ME85-01-00-00-00
Is Prebook No
GPS Codes 9800-A6,9807-A6,9813-A6,9694,9968-A6,9AF6-A6,9B13-A6

European and North American Advanced Driver Assistance Systems (ADAS) and High Definition (HD) Mapping Market, 2018

AutomotiveEuropean and North American Advanced Driver Assistance Systems (ADAS) and High Definition (HD) Mapping Market, 2018 Updated Research Available

Start-ups, With Their Innovative Business Model Will End the Dominance of Traditional Map Developers

RELEASE DATE
09-Apr-2019
REGION
North America
Deliverable Type
Market Research
Research Code: ME85-01-00-00-00
SKU: AU01822-NA-MR_23010
AvailableYesPDF Download
$4,950.00
In stock
SKU
AU01822-NA-MR_23010